Marketing Research (Key Concepts) PDF

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Marketing Research: Key Concepts 1) Marketing information system (MIS): A marketing information system (MIS) is a formalized set of procedures for generating, analysing, storing, and distributing pertinent information to marketing decision-makers on an ongoing basis. 2) Marketing research: Research is the systematic and objective identification, collection, analysis, dissemination, and use of information for the purpose of improving decision-making related to the identification and solution of problems and opportunities in marketing. 3) An example of marketing research failure: Johnson & Johnson is considered to be the world’s most broadly based manufacturer of health care products. Despite its success in the industry, Johnson & Johnson’s attempt to use its company name on baby aspirin proved to be unsuccessful. Johnson & Johnson baby products are perceived as gentle, but gentleness is not what people want in a baby aspirin. This is an example of what intuitively seemed to be a natural move but without proper marketing research turned out to be an incorrect decision 4) Flowchart of marketing research process: The marketing research process refers to a set of six steps that defines the tasks to be accomplished in conducting a marketing research study. - Step 1: Problem Definition: In defining the problem, the researcher should take into account the purpose of the study, the relevant background information, the information needed, and how it will be used in decision making. - Step 2: Development of an Approach to the Problem: Development of an approach to the problem includes formulating an objective or theoretical framework, hypotheses and identifying the information needed. - Step 3: Research Design Formulation A research design is a framework or blueprint for conducting the marketing research project. It details the procedures necessary for obtaining the required information, and its purpose is to design a study that will test the hypotheses of interest. - Step 4: Fieldwork or Data Collection: Data collection involves a field force or staff that operates either in the field, as in the case of personal interviewing or electronically. - Step 5: Data Preparation and Analysis: Data preparation includes the editing, coding, transcription, and verification of data. Each questionnaire or observation form is inspected or edited and, if necessary, corrected. - Step 6: Report Preparation and Presentation: The entire project should be documented in a written report that addresses the specific research questions identified; describes the approach, data analysis procedures adopted and presents the results. 5) Decision problems versus research problems: The management decision problem asks what the decision-maker (DM) needs to do, whereas the marketing research problem asks what information is needed and how it can best be obtained. 6) Research design: A research design is a framework or blueprint for conducting the marketing research project. It details the procedures necessary for obtaining the required information, and its purpose is to design a study that will test the hypotheses of interest.. More formally, formulating the research design involves the following steps: 1. Definition of the information needed 2. Secondary data analysis 3. Qualitative research 4. Methods of collecting quantitative data (survey, observation, and experimentation) 5. Measurement and scaling procedures 6. Questionnaire design 7. Sampling process and sample size 8. Plan of data analysis 7) Types of marketing research and research methods 1. Exploratory Research: discover ideas that may be potential business opportunities

2. Descriptive Research: describes characteristics of objects, people, groups, organizations or environments. 3. Causal Research: allows causal inferences to be made and they identify cause-and effect relationship. 8) Advantages using secondary data: These data can be located quickly and inexpensively. Secondary data can help you: - Identify the problem. - Better define the problem. - Develop an approach to the problem. - Formulate an appropriate research design (for example, by identifying the key variables). - Answer certain research questions and test some hypotheses. - Interpret primary data more insightfully. 9) Disadvantages using secondary data: because secondary data have been collected for purposes other than the problem at hand, their usefulness to the current problem may be limited in several important ways, including relevance and accuracy 10) Sources of secondary data: Secondary data may be classified as either internal or external. Internal data are those generated within the organization for which the research is being conducted. External data are those generated by sources outside the organization. These data may exist in the form of published material, computerized databases, or information made available by syndicated services. 11) Globalisation on big data research: a wide variety of secondary data are available for international marketing research, the problem is not one of lack of data but of the plethora of information available, and it is useful to classify the various sources. Secondary international data are available from both domestic government and nongovernment sources. 12) Qualitative versus quantitative data: Qualitative research refers to an unstructured, exploratory research methodology based on small samples that provides insights and understanding of the problem setting. Quantitative research mandates a research methodology that seeks to quantify the data and, typically, applies some form of statistical analysis. 13) Phenomenology: A philosophical approach to studying human experiences based on the idea that human experience itself is inherently subjective and determined by the context in which people live. The experience is down to the individual making it subjective, will have to rely in conversational interviews 14) Ethnography: Represents ways of studying cultures through methods that involve becoming highly active within that culture 15) Grounded theory: Represents an inductive investigation in which the researcher poses questions about information provided by respondents or taken from historical records. 16) Focus Groups: A focus group is an interview conducted by a trained moderator in a nonstructured and natural manner with a small group of respondents. Focus groups can be used to address substantive issues such as: 1. Understanding consumers’ perceptions, preferences, and behaviour concerning a product category. 2. Obtaining impressions of new product concepts 3. Generating new ideas about older products 4. Developing creative concepts and copy material for advertisements 5. Securing price impressions 17) Depth Interviews: Depth interviews are an unstructured and direct way of obtaining information, but unlike focus groups, depth interviews are conducted on a one-on-one basis. A depth interview is where a single respondent is probed by a highly skilled interviewer to uncover feelings on a topic.

18) Observations: Observation involves recording the behavioural patterns of people, objects, and events in a systematic manner to obtain information about the phenomenon of interest. 19) Ethics in qualitative research: When conducting qualitative research, ethical issues related to the respondents and the general public are of primary concern. These issues include disguising the purpose of the research and the use of deceptive procedures, videotaping and recording the proceedings, the comfort level of the respondents, and misusing the findings of qualitative research. All indirect procedures require disguising the purpose of the research, at least to some extent. Often, a cover story is used to camouflage the true purpose. This can violate the respondents’ right to know and also result in psychological harm. 20) Errors in survey research: Disadvantages are that respondents may be unable or unwilling to provide the desired information. For example, consider questions about motivational factors. Respondents may be unwilling to respond if the information requested is sensitive or personal. Also, structured questions and fixed-response alternatives may result in loss of validity for certain types of data such as beliefs and feelings. Finally, wording questions properly is not easy. Yet, despite these disadvantages, the survey approach is by far the most common method of primary data collection in marketing research 21) Survey questionnaires may be administered in four major modes: (1) telephone interviews, (2) personal interviews, (3) mail interviews, and (4) electronic interviews. Telephone interviews may be further classified as traditional telephone interviews or computer-assisted telephone interviews (CATI). 22) Basic characteristics of research experiments a) Causal Research: Research designs can be exploratory (when the objective is to discover new ideas and insights), descriptive (when the objective is to describe market characteristics), or causal. Causal research seeks to determine cause-and-effect relationships. b) Controlling Extraneous Variables: Randomization is also a method for controlling extraneous variables in experiments. It involves randomly assigning test units (such as stores or consumers) and independent variables to different experimental groups. Another method involves matching or comparing test units on a set of key background variables before assigning them to an experimental group. statistical control can be implemented by measuring extraneous variables and adjusting for their effects during analysis using statistical techniques. Finally, experiments specifically designed to control for extraneous variables can be used, known as design control. c) Difference Between Lab and Field Experiments: There are both advantages and disadvantages for using either lab or field experiments, so you’ll need to weigh the trade-offs and determine which is best for fulfilling your research objectives, or if you want to employ both in a complimentary design. d) Test Marketing Basics: Test marketing replicates a planned national marketing program completed on a small scale in a carefully selected limited number of test markets. er kinds of test marketing include controlled test marketing in which the entire program is conducted by an outside research company – guaranteeing distribution in a predetermined percentage of the market – and simulated test marketing in which consumers are intercepted in high-traffic locations like malls, pre-screened for product usage, given the opportunity to purchase a product in either a real or lab setting, and interviewed post-product usage. 23) Internal Validity: Is the experimental variable truly responsible for any variance in the dependent variable. 24) External Validity: Behavioural experiments often involve the use of convenient subjects rather than individuals randomly selected. 25) Test Marketing: Test marketing is defined as a strategy used by companies to check the viability of their new product or a marketing campaign before it is launched in the market on a large scale.

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Ethics in experimental research: the use of survey research as a guise for selling (called sugging in the trade language) or fundraising (frugging) is unethical. Another ethical issue that is salient in survey and observation research is respondents’ anonymity. Levels of Measurement: There are four primary levels of scales of measurement: nominal, ordinal, interval, and ratio. - Nominal: Nominal scale is a scale whose numbers serve only as labels or tags for identifying and classifying objects. When used for identification, there is a strict one-to-one correspondence between the numbers and the objects. - Ordinal: An ordinal scale is a ranking scale in which numbers are assigned to objects to indicate the relative extent to which some characteristic is possessed. Thus it is possible to determine whether an object has more or less of a characteristic than some other object. - Interval: In an interval scale, numerically equal distances on the scale represent equal values in the characteristic being measured. An interval scale contains all the information of an ordinal scale, but it also allows you to compare the differences between objects. The difference between any two scale values is identical to the difference between any other two adjacent values of an interval scale. - Ratio: A ratio scale possesses all the properties of the nominal, ordinal, and interval scales and, in addition, an absolute zero point. Thus, ratio scales possess the characteristic of origin (and distance, order, and description). Thus, in ratio scales we can identify or classify objects, rank the objects, and compare intervals or differences. Types of scales - Noncomparative Scale: Respondents using a noncomparative scale employ whatever rating standard seems appropriate to them. - Continuous rating Scale: In a continuous rating scale, also referred to as a graphic rating scale, respondents rate the objects by placing a mark at the appropriate position on a line that runs from one extreme of the criterion variable to the other. - Itemized rating Scale: In an itemized rating scale, the respondents are provided with a scale that has a number or brief description associated with each category. - Multi-item Scales: A multi-item scale consists of multiple items, where an item is a single question or statement to be evaluated. The Likert, semantic differential, and Stapel scales presented earlier to measure attitudes toward Sears are examples of multi-item scales. Reliability: Reliability refers to the extent to which a scale produces consistent results if repeated measurements are made. Systematic sources of error do not have an adverse impact on reliability, because they affect the measurement in a constant way and do not lead to inconsistency. Validity: The validity of a scale may be defined as the extent to which differences in observed scale scores reflect true differences among objects on the characteristic being measured, rather than systematic or random error. The relationship between reliability and validity can be understood in terms of the true score model. If a measure is perfectly valid, it is also perfectly reliable. Questionnaire design: Questionnaire design will be presented as a series of steps. These steps are; 1) specify the information needed, 2) specify the type of interviewing method, 3) determine the content of individual questions, 4) design the questions to overcome the respondent’s inability and unwillingness to answer, (5) decide on the question structure, 5) determine the question wording, 6) arrange the questions in proper order, 7) identify the form and layout, 8) reproduce the questionnaire, and

9) pretest the questionnaire. 32) Sampling techniques may be broadly classified as nonprobability and probability, in probability sampling, sampling units are selected by chance. It is possible to prespecify every potential sample of a given size that could be drawn from the population, as well as the probability of selecting each sample. Nonprobability sampling relies on the personal judgment of the researcher rather than chance to select sample elements. The researcher can arbitrarily or consciously decide what elements to include in the sample. 33) Fieldwork process: All fieldwork involves the selection, training, and supervision of persons who collect data. The process involves 5 stages (1) Selection of Fieldworkers: The first step in the fieldwork process is the selection of fieldworkers. The researcher should: (1) develop job specifications for the project, taking into account the mode of data collection; (2) decide what characteristics the fieldworkers should have; and (3) recruit appropriate individuals. (2) Training of Fieldworkers: Training of fieldworkers is critical to the quality of data collected. Training ensures that all interviewers administer the questionnaire in the same manner so that the data can be collected uniformly. (3) Supervision of fieldworkers: Supervision of fieldworkers means making sure that they are following the procedures and techniques in which they were trained. Supervision involves quality control and editing, sampling control, control of cheating, and central office control. (4) Validation of fieldwork: Validation of fieldwork means verifying that the fieldworkers are submitting authentic interviews. To validate the study, the supervisors call 1025% of the respondents to inquire whether the fieldworkers actually conducted the interviews. The supervisors ask about the length and quality of the interview, reaction to the interviewer, and basic demographic data. The demographic information is cross-checked against the information reported by the interviewers on the questionnaires (5) Evaluation of fieldworkers:It is important to evaluate fieldworkers to provide them with feedback on their performance as well as to identify the better fieldworkers and build a better, high-quality field force. 34) Descriptive statistics: Descriptive statistics are used to describe or summarize the characteristics of a sample or data set, such as a variable's mean, standard deviation, or frequency. 35) Tabulation: Cross-tabulation is a method to quantitatively analyse the relationship between multiple variables. 36) Hypothesis Testing: A general procedure for hypothesis testing that can be applied to test hypotheses about a wide range of parameters (1) Formulate the null hypothesis H0 and the alternative hypothesis H1. (2) Select an appropriate statistical technique and the corresponding test statistic. (3) Choose the level of significance, . (4) Determine the sample size and collect the data. Calculate the value of the test statistic. (5) Determine the probability associated with the test statistic under the null hypothesis, using the sampling distribution of the test statistic. (6) Compare the probability associated with the test statistic with the level of significance specified. (7) Make the statistical decision to reject or not reject the null hypothesis. (8) Express the statistical decision in terms of the marketing research problem. 34) Type I error: Occur when the sample results lead to the rejection of the null hypothesis when it is in fact true. The probability of Type I error is also called the level of significance. 35) Type II error: Occurs when, based on the sample results, the null hypothesis is not rejected when it is in fact false.

36) Three types of t-test: A t-test is a univariate hypothesis test using the t distribution, which is used when the standard deviation is unknown, and the sample size is small One Sample: When null hypotheses can be tested using a one-sample test, such as the t test or the z test. Two Independent Samples: Two-Independent-Samples t-test may be performed if it is known whether the two populations have equal variance. Paired Samples: two sets of observations relate to the same respondents. The difference in these cases is examined by a paired samples t test. 37) ANOVA: Analysis of variance (ANOVA) is used as a statistical technique for examining the differences among means for two or more populations. 38) One-way ANOVA: One-way analysis of variance involves only one categorical variable, or a single factor. Interest lies in testing the null hypothesis that the category means are equal in the population. 39) Correlation: A measure of association capturing how much one variable changes as another variable(s) changes. 40) Regression: defined as the straight line fitted onto a set of data points that minimises the sum of the squared errors (residuals). 41) Effect size: Effect sizes are often measured in terms of the proportion of variance explained by a variable....